A reexamination of the market efficiency hypothesis: Evidence from an electronic intra-day,inter-dealer FX market

Researchers acknowledge that the evidence of autocorrelation (price dependency) in daily/weekly asset returns provides no conclusive evidence against the market efficiency hypothesis since the holding period of actual speculative positions may be less than a day. Using a high frequency (up to one hundredth of a second), transaction-based, electronic foreign exchange (FX) brokerage data set, we show that dealers in this market tend to close their speculative positions in less than a minute. We provide evidence that there is a significant negative autocorrelation in the rate of return on DM/USD exchange rate. However, when we sample data at frequencies shorter than a minute, profits are infeasible for two reasons: (1) the structure of the autocorrelation pattern is not consistent enough; (2) the largest potential speculative profit derived from the autocorrelation pattern is smaller than the regulated tick size. Our results support the market efficiency hypothesis as dealers have evidently engaged potentially profitable speculation based on price dependency.     

Nonlinear deterministic forecasting of daily dollar exchange rates

We perform out-of-sample predictions on several dollar exchange rate returns by using time-delay embedding techniques and a local linear predictor. We compared our predictions with those by a mean value predictor. Some of our predictions of the exchange rate returns outperform the predictions of the same series by the mean value predictor. However, these improvements were not statistically significant. Another interesting result in this paper which was obtained by using a recently developed technique of nonlinear dynamics is that all exchange rate return series we tested have a very high embedding dimension. Additionally, evidence indicates that these series are likely generated by high dimensional systems with measurement noise or by high dimensional nonlinear stochastic systems, that is, nonlinear deterministic systems with dynamic noise.     

On the distribution of the sample autocorrelation coefficients

Sample autocorrelation coefficients are widely used to test the randomness of a time series. Despite its unsatisfactory performance, the asymptotic normal distribution is often used to approximate the distribution of the sample autocorrelation coefficients. This is mainly due to the lack of an efficient approach in obtaining the exact distribution of sample autocorrelation coefficients. In this paper, we provide an efficient algorithm for evaluating the exact distribution of the sample autocorrelation coefficients. Under the multivariate elliptical distribution assumption, the exact distribution as well as exact moments and joint moments of sample autocorrelation coefficients are presented. In addition, the exact mean and variance of various autocorrelation-based tests are provided. Actual size properties of the Box–Pierce and Ljung–Box tests are investigated, and they are shown to be poor when the number of lags is moderately large relative to the sample size. Using the exact mean and variance of the Box–Pierce test statistic, we propose an adjusted Box–Pierce test that has a far superior size property than the traditional Box–Pierce and Ljung–Box tests.     

The dynamic relationship between stock,bond and foreign exchange markets

This paper investigates whether the deviation of a currency from its fundamentally determined rate of return affects the relationship between interest rates and stock market yields. A time-varying transition probability, the Markov-switching vector autoregressive (MS-VAR) model, is utilized for this purpose. Wald and likelihood ratio tests are computed and used as model adequacy measures. In order to analyze the link between the variables, impulse–response functions are employed. A sticky price exchange rate model is used to show the fundamentally determined rate of return of currencies. States are defined as either overvalued or undervalued, depending on the position of the observed exchange rate compared to its fundamentally determined rate. The model is applied to four major currencies: the Australian Dollar, the Canadian Dollar, the Japanese Yen, and the British Pound. Transition between the states is linked to the risk-adjusted excess return (the Sharpe ratio) of the debt and equity markets of the respective currencies in order to understand whether over- and undervaluation is connected to the returns in these markets. The results provide evidence that the relationship between economic fundamentals and nominal exchange rates are subject to change depending on the over- or undervaluation of the currencies relative to their fundamentally determined rate of return. An extension of this result shows that the Sharpe ratios of debt and equity investments in the currencies influence the evolution of the transitional dynamics of the exchange rates’ deviation from their fundamental values.     

Nonlinear dynamics and recurrence plots for detecting financial crisis

Identification of financial bubbles and crisis is a topic of major concern since it is important to prevent collapses that can severely impact nations and economies. Our analysis deals with the use of the recently proposed ⿿delay vector variance⿿ (DVV) method, which examines local predictability of a signal in the phase space to detect the presence of determinism and nonlinearity in a time series. Optimal embedding parameters used in the DVV analysis are obtained via a differential entropy based method using wavelet-based surrogates. We exploit the concept of recurrence plots to study the stock market to locate hidden patterns, non-stationarity, and to examine the nature of these plots in events of financial crisis. In particular, the recurrence plots are employed to detect and characterize financial cycles. A comprehensive analysis of the feasibility of this approach is provided. We show that our methodology is useful in the diagnosis and detection of financial bubbles, which have significantly impacted economic upheavals in the past few decades.     

A GUIDED TOUR OF THE MARKET MICROSTRUCTURE APPROACH TO EXCHANGE RATE DETERMINATION

Abstract.  We propose a critical review of recent developments in exchange rate economics which have offered a novel approach to exchange rate determination. This new strand of research, the market microstructure approach to exchange rates, is motivated by some very stark empirical evidence, relating exchange rate dynamics to the imbalance in the sequence of purchases and sales of foreign currencies in the markets for foreign exchange. Through our review we outline the results this new strand of research has achieved alongside its open questions and future challenges.     

THE DYNAMICS OF REAL EXCHANGE RATES: A RECONSIDERATION

In this paper we offer a bootstrap‐based version of the Cox specification test for non‐nested hypothesis to discriminate between ESTAR and MSAR models. Both models are commonly used for modeling real exchange rates dynamics. We show that the test has good size and power properties in finite samples. In an application, we analyze several major real exchange rates to shed light on the question of which model describes these processes best. This allows us to draw conclusions about the driving forces of real exchange rates. Copyright © 2013 John Wiley & Sons, Ltd.     

Factors affecting secondary share offerings in the IPO process

We investigate whether the sale of secondary shares in the IPO process is affected by an issuing firm's market-timing and window-dressing activities. We find that secondary share offerings in IPOs exhibit positive autocorrelation, and the positive autocorrelation is mainly affected by the overall stock market return. Similar to the IPO wave, this finding suggests that favorable market conditions attract existing pre-IPO shareholders to sell their shares in IPOs and cause the clustering of secondary share offering in IPOs. In addition, we find that window dressing has a significant effect on both the probability of secondary share offering and the proportion of secondary shares offered in an IPO. The result is robust after controlling for firm age, industry affiliation, and other factors. Our result also indicates that the number of firms offering secondary shares in IPOs, the probability of secondary share offerings, and the proportion of secondary shares offered in IPOs are significantly lower in the Internet bubble period.     

Disagreement with procyclical beliefs and asset pricing

We consider a pure exchange economy with incomplete information in which the expected growth rate of endowment is unobservable. The economy is populated by two investors, one is rational, but the other irrationally believes that the dynamics of endowment exhibit procyclical feature. Such different opinions about the dynamics of endowment process produce persistent disagreement between the investors. We show that model-implied riskfree rate is procyclical. Further, the procyclical beliefs not only explain the excess volatility puzzle, but also help to explain the mixed results about the relationship between the investors’ belief dispersions and stock return. Moreover, we uncover that the rational investor prefers to short stock positions in good times as the degree of the other investor’s irrationality increasing.     

Testing for convergence: evidence from non-parametric multimodality tests

In this paper, we test the convergence hypothesis in a cross-section of 119 countries by means of bootstrap multimodality tests and nonparametric density estimation techniques. By looking at the density distribution of GDP across countries in 1970, 1980 and 1989, we find low mobility patterns of intra-distribution dynamics and increasing evidence for bimodality. The findings stand in sharp contrast with the convergence prediction. © 1997 John Wiley & Sons, Ltd.     

Bootstrapping Financial Time Series

It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations may be inadequate. As bootstrap methods are not, in general, based on any particular assumption on the distribution of the data, they are well suited for the analysis of returns. This paper reviews the application of bootstrap procedures for inference and prediction of financial time series. In relation to inference, bootstrap techniques have been applied to obtain the sample distribution of statistics for testing, for example, autoregressive dynamics in the conditional mean and variance, unit roots in the mean, fractional integration in volatility and the predictive ability of technical trading rules. On the other hand, bootstrap procedures have been used to estimate the distribution of returns which is of interest, for example, for Value at Risk (VaR) models or for prediction purposes. Although the application of bootstrap techniques to the empirical analysis of financial time series is very broad, there are few analytical results on the statistical properties of these techniques when applied to heteroscedastic time series. Furthermore, there are quite a few papers where the bootstrap procedures used are not adequate.     

Economic policy uncertainty and industry risk on China’s stock market

We propose a dynamic mixture Copula with time-varying weight, which is endowed with generalized autoregressive score dynamics. Based on this model, we portray the lower-tail dependence between the return of WIND first-level industry and CSI-300 index as a proxy variable for the industry risk in China’s stock market, and use the VAR-GARCH-in-mean model based on BEKK-GARCH to deconstruct the different impact of the economic policy uncertainty (EPU) on industry risk of the first and second moments in terms of four policy categories, namely fiscal policy, monetary policy, trade policy, and foreign exchange rate and capital account policy. The results are followed. Firstly, the risk of Consumer Discretionary is averagely the highest, while the risk of Utilities remains the lowest. Secondly, category-specific EPU has no significant mean spillover to the risk of overall industries, while the variance spillover is significant for all the cases. Thirdly, except for Real Estate, the GARCH-in-mean effect is not significant of EPU on industry risks. Further more, all those three kinds of impact show industrial heterogeneities. To avoid systemic risks, we advise that the issue of economic policy should be forward-looking, consistent, and targeted, especially for sensitive industries.     

Prediction regions for interval-valued time series

We approximate probabilistic forecasts for interval-valued time series by offering alternative approaches. After fitting a possibly non-Gaussian bivariate vector autoregression (VAR) model to the center/log-range system, we transform prediction regions (analytical and bootstrap) for this system into regions for center/range and upper/lower bounds systems. Monte Carlo simulations show that bootstrap methods are preferred according to several new metrics. For daily S&P 500 low/high returns, we build joint conditional prediction regions of the return level and volatility. We illustrate the usefulness of obtaining bootstrap forecasts regions for low/high returns by developing a trading strategy and showing its profitability when compared to using point forecasts.     

Dynamic spillovers and linkages between gold,crude oil,S&P 500, and other economic and financial variables. Evidence from the USA

This paper focuses on the price determinants of gold, and on the challenges associated with gold’s safe haven property. Specifically, it analyses the interlinkages and the return spillover effect among gold, crude oil, S&P 500, dollar exchange rate, Consumer Price Index (CPI), economic policy uncertainty and Treasury bills, by employing a Vector Autoregression (VAR) and the spillover index of Diebold and Yilmaz (2012), Diebold and Yılmaz (2014). Monthly realized return series, covering the period from 2nd of January 1986 to 31st of December 2019 are used to examine the short-run linkages, and the return spillovers rolling-window estimates in analyzing the transmission mechanism in a time-varying fashion, respectively. Our findings identify gold as a strong dollar hedge, while crude oil and Treasury bills appear to drive inflation; they also indicate strong spillover effects between exchange rate and gold returns. In general, co-movement dynamics display state-dependent characteristics. Both total and directional spillovers increase significantly during market turbulence caused by severe financial crises such as the Global Financial Crisis (GFC) of 2007–2009 and the European Sovereign Debt Crisis of 2010–2012. Net spillovers switch between positive and negative values for all these markets, implying that the recipient/transmitter position changes drastically with market events. Economic policy uncertainty, stock market returns, and crude oil price returns are the main transmitters, while Treasury bills and CPI are the main return shock recipients. Gold and exchange rate act both as receivers and transmitters over the sample period.     

一种汽车后侧推拉窗的设计及问题分析

文章介绍了某汽车公司一款微型车后侧推拉窗设计所使用的密封结构,即后侧窗固定玻璃、滑动玻璃与窗框胶条、中间密封条之间的配合衔接关系,并对其设计过程遇到的问题进行分析和解剖。     

Bootstrapping rank statistics

The bootstrap, which provides powerful approximations for many classes of statistics, is studied for simple linear rank statistics employing bounded and smooth score functions. To verify consistency we view a rank statistic as a statistic induced by a statistical functional ψ which is evaluated at a pair of dependent signed measures. Thus, we can apply the von Mises method to verify asymptotic results for the bootstrap. The strong consistency of the bootstrap distribution estimator is derived for the bootstrap based on resampling from the original data. Further, the residual bootstrap is studied. The accuracy of the bootstrap approximations for small sample sizes is studied by simulations. The simulations indicate that the bootstrap provides better results than a normal approximation.     

Bootstrapping Confidence Intervals for Linear Programming Efficiency Scores: With an Illustration Using Italian Banking Data

This article suggests a method for introducing a stochastic element into Farrell measures of technical efficiency as calculated via linear programming techniques. Specifically, a bootstrap of the original efficiency scores is performed to derive confidence intervals and a measure of bias for the scores. The bootstrap generates these measures of statistical precision for the nonstochastic efficiency measures by using computational power to derive empirical distributions for the efficiency measures.     

Do European business cycles look like one?

This paper provides a comprehensive framework to analyze business cycle features other than synchronization. We use stationary bootstrap and model-based clustering methods to analyze similarities and differences among the European cycles. We find evidence that the length, deep and shape of cycles differ across European countries and that these differences are not decreasing over time. Finally, even though we find some correlation between business cycle synchronization and characteristics, there is important information in the characteristics that is not captured by the synchronization measures.     

ARIMA融合神经网络的人民币汇率预测模型研究

本文在深入分析了单整自回归移动平均(ARIMA)模型与神经网络(NN)模型特点的基础上,建立了ARIMA融合NN的人民币汇率时间序列预测模型。其基本思想是充分发挥两种模型在线性空间和非线性空间的预测优势,即将汇率时间序列的数据结构分解为线性自相关主体和非线性残差两部分,首先用ARI-MA模型预测序列的线性主体,然后用NN模型对其非线性残差进行估计,最终合成为整个序列的预测结果。通过对三种人民币汇率序列的仿真实验表明,融合模型的预测准确率显著高于包括随机游走模型在内的单一模型的预测准确率,从而证实了融合模型用于汇率预测的有效性。这一结果也表明,人民币汇率市场并不符合有效市场假设,可以通过模型对汇率未来走势做出较准确预测。     

Valuation effects of capital inflows: Evidence from emerging market economies

This paper studies valuation changes of capital inflows in 19 emerging market economies (EMEs). In most of the EMEs, we find that there are significant valuation changes and a positive rate of return on external liabilities by foreigners. Furthermore, the nonlinear effects of exchange rate movements on valuation changes are investigated using panel smooth transition regression models. Empirical results show that the transition is centered at approximately −22.3% of exchange rate change, which implies that when the exchange rate appreciates more than this level, foreign investment value gains increase considerably.